The present invention generally relates to object recognition and, more particularly, to systems and method for automatically detecting objects based on pattern recognition and weight measurement.
In many retail store environments, such as in grocery stores, department stores, office supply stores, home improvements stores, and the like, consumers use shopping carts to carry merchandise. Upon entering a check out lane, a shopper must frequently unload the merchandise, and place the merchandise on a conveyor belt so that a store clerk can pick up each item, rotate the merchandise until a bar code is found, and then position the bar code in front of a reader. This results in delays for both the shopper and store. In turn, this can result in lost revenue to the store inasmuch as revenue is dependent upon the speed at which the store can get shoppers through a check out line.
One of the goals within the retail industry has been to design the checkout stand in a manner that can expedite the checkout process and provide convenience to the customers and the cashier. In an effort to increase throughput and checkout efficiency, several self-checkout systems have been developed for retail environments. Self-checkout systems, such as those marketed by Fujitsu, Inc. <URL: http://www.ftxs.fujitsu.com>, operate like conventional checkout systems with a difference that these systems have the customer replace the cashier, and as a consequence, may reduce labor and turnover costs. The self-checkout system marketed by Fujitsu operates as a point-of-sale. To process transactions of the items to be checked out, the customer may scan the UPC of each item and put the item on a weighing scale. Then, the self-checkout system looks up a database to get the weight data of the item. If the weight data of the item matches the reading of the weighing scale, the item is added to a checkout list. Thus, these existing self-checkout systems rely on customers to process the merchandise. Typically, the customers are not as experienced as the cashiers in processing the merchandise, and as a consequence, exiting self-checkout systems may be slower in processing the merchandise than the conventional checkout systems. This can result in lost revenue to the store negating the savings in cashier's labor cost if revenue is dependent upon the checkout speed.
As can be noticed, a self-checkout system can yield high throughput and reduce labor and turnover costs if the system can detect and recognize items in the absence of a user needing to physically scan UPCs and/or weigh the items individually. Thus, there is a need for an improved apparatus and methods that can recognize items for self-checkout of merchandise in the absence of a user's intervention to scan the UPC and/or weigh each item.